Machine intelligence is useful to gain insights to a large quantity of data that is undecipherable to human comprehension. Machine intelligence, also known as artificial intelligence, can encompass machine learning analysis, natural language parsing and processing, computer perception, or any combination thereof. These technical means can facilitate studies and researches yielding specialized insights that are normally not attainable by human mental exercises. Subject matter that is circulated widely (e.g., share with users online “friends” as Prentice said to be “trending” or “going viral.”
Machine intelligence can be used to analyze digital conversations, publications, or other user-generated content from human beings. The digital conversations, publications, or other user-generated content can be collectively referred to as digital “chatter.” For example, the machine intelligence can identify characteristics, including viral trends, of the digital conversations that are pertinent in making decisions in a social networking system. Various aspects of the social networking system can benefit from knowing whether certain subject matter in the social networking system has gone or is going viral. Yet because of the nature of viral content, computationally, it is expensive and challenging to timely identify user activities that are contributing to viral propagation of content.
The figures show various embodiments of this disclosure for purposes of illustration only. One skilled in the art will readily recognize from the following discussion that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of embodiments described herein.